Separating clinical antibodies from repertoire antibodies, a path to in silico developability assessment. Issue 1 (31st December 2022)
- Record Type:
- Journal Article
- Title:
- Separating clinical antibodies from repertoire antibodies, a path to in silico developability assessment. Issue 1 (31st December 2022)
- Main Title:
- Separating clinical antibodies from repertoire antibodies, a path to in silico developability assessment
- Authors:
- Negron, Christopher
Fang, Joyce
McPherson, Michael J.
Stine, W. Blaine
McCluskey, Andrew J. - Abstract:
- ABSTRACT: Approaches for antibody discovery have seen substantial improvement and success in recent years. Yet, advancing antibodies into the clinic remains difficult because therapeutic developability concerns are challenging to predict. We developed a computational model to simplify antibody developability assessment and enable accelerated early-stage screening. To this end, we quantified the ability of hundreds of sequence- and structure-based descriptors to differentiate clinical antibodies that have undergone rigorous screening and characterization for drug-like properties from antibodies in the human repertoire that are not natively paired. This analysis identified 144 descriptors capable of distinguishing clinical from repertoire antibodies. Five descriptors were selected and combined based on performance and orthogonality into a single model referred to as the Therapeutic Antibody Developability Analysis (TA-DA). On a hold-out test set, this tool separated clinical antibodies from repertoire antibodies with an AUC = 0.8, demonstrating the ability to identify developability attributes unique to clinical antibodies. Based on our results, the TA-DA score may serve as an approach for selecting lead antibodies for further development. Abbreviations: Affinity-Capture Self-Interaction Nanoparticle Spectroscopy (AC-SINS), Area Under the Curve (AUC), Complementary-Determining Region (CDR), Clinical-Stage Therapeutics (CST), Framework (FR), Monoclonal Antibodies (mAbs),ABSTRACT: Approaches for antibody discovery have seen substantial improvement and success in recent years. Yet, advancing antibodies into the clinic remains difficult because therapeutic developability concerns are challenging to predict. We developed a computational model to simplify antibody developability assessment and enable accelerated early-stage screening. To this end, we quantified the ability of hundreds of sequence- and structure-based descriptors to differentiate clinical antibodies that have undergone rigorous screening and characterization for drug-like properties from antibodies in the human repertoire that are not natively paired. This analysis identified 144 descriptors capable of distinguishing clinical from repertoire antibodies. Five descriptors were selected and combined based on performance and orthogonality into a single model referred to as the Therapeutic Antibody Developability Analysis (TA-DA). On a hold-out test set, this tool separated clinical antibodies from repertoire antibodies with an AUC = 0.8, demonstrating the ability to identify developability attributes unique to clinical antibodies. Based on our results, the TA-DA score may serve as an approach for selecting lead antibodies for further development. Abbreviations: Affinity-Capture Self-Interaction Nanoparticle Spectroscopy (AC-SINS), Area Under the Curve (AUC), Complementary-Determining Region (CDR), Clinical-Stage Therapeutics (CST), Framework (FR), Monoclonal Antibodies (mAbs), Observed Antibody Space (OAS), Receiver Operating Characteristic (ROC), Size-Exclusion Chromatography (SEC), Structural Aggregation Propensity (SAP), Therapeutic Antibody Developability Analysis (TA-DA), Therapeutic Antibody Profiler (TAP), Therapeutic Structural Antibody Database (Thera-SAbDab), Variable Heavy (VH), Variable Light (VL). … (more)
- Is Part Of:
- MAbs. Volume 14:Issue 1(2022)
- Journal:
- MAbs
- Issue:
- Volume 14:Issue 1(2022)
- Issue Display:
- Volume 14, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 14
- Issue:
- 1
- Issue Sort Value:
- 2022-0014-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-12-31
- Subjects:
- Developability -- drug discovery -- machine learning -- repertoire antibodies -- therapeutic antibodies
Monoclonal antibodies -- Therapeutic use -- Periodicals
Monoclonal antibodies -- Periodicals
Antibodies, Monoclonal -- Periodicals
616.0798 - Journal URLs:
- http://www.tandfonline.com/loi/kmab20#.VufTUVLcuic ↗
http://www.landesbioscience.com/journals/mabs ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/19420862.2022.2080628 ↗
- Languages:
- English
- ISSNs:
- 1942-0862
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5320.243000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 22269.xml